The present invention relates to computed tomography (CT) imaging and, more particularly, to systems and methods for energy domain data correction in spectral CT imaging to control noise and radiation dose.
In a computed tomography system, an x-ray source projects a fan or cone shaped beam which is collimated to lie within an X-Y plane of a Cartesian coordinate system, termed the “imaging plane.” The x-ray beam passes through the object being imaged, such as a medical patient or other non-medical patient or object, such as in industrial CT imaging, and impinges upon an array of radiation detectors. The intensity of the transmitted radiation is dependent upon the attenuation of the x-ray beam by the object and each detector produces a separate electrical signal that is a measurement of the beam attenuation. The attenuation measurements from all the detectors are acquired separately to produce the transmission profile at a particular view angle.
The source and detector array in a conventional CT system are rotated on a gantry within the imaging plane and around the object so that the angle at which the x-ray beam intersects the object constantly changes. A group of x-ray attenuation measurements from the detector array at a given angle is referred to as a “view”, and a “scan” of the object comprises a set of views acquired at different angular orientations during one revolution of the x-ray source and detector. In a 2D scan, data is processed to construct an image that corresponds to a two dimensional slice taken through the object. The prevailing method for reconstructing an image from 2D data is referred to in the art as the filtered backprojection technique, however, other image reconstruction processes are also well known. This process converts the attenuation measurements from a scan into integers called “CT numbers” or “Hounsfield units”, which are used to control the brightness of a corresponding pixel on a display.
The term “generation” is used in CT to describe successively commercially available types of CT systems utilizing different modes of scanning motion and x-ray detection. More specifically, each generation is characterized by a particular geometry of scanning motion, scanning time, x-ray beam shape, and detector system.
The first generation utilized a single linear x-ray beam (“pencil beam”) and a single scintillation crystal-photomultiplier tube detector for each tomographic slice. After a single linear motion or traversal of the x-ray tube and detector, during which time 160 separate x-ray attenuation or detector readings are typically taken, the x-ray tube and detector are rotated through one degree and another linear scan is performed to acquire another view. This is repeated typically to acquire 180 views.
A second generation of CT systems was developed to shorten the scanning times of first generation systems by gathering the attenuation data more quickly. In these units, a modified fan beam, including anywhere from 3-52 individual collimated x-ray beams, and a number of detectors equal to the number of collimated x-ray beams are used. Individual beams resemble the single beam of a first generation scanner; however, a collection of from 3-52 of these beams contiguous to one another allows multiple adjacent regions of tissue to be examined simultaneously. The configuration of these contiguous regions of tissue resembles a fan, with the thickness of the fan material determined by the collimation of the beam and in turn determining the slice thickness. Because of the angular difference of each beam relative to the others, several different angular views through the body slice are being examined simultaneously. Superimposed on this is a linear translation or scan of the x-ray tube and detectors through the body slice. Thus, at the end of a single translational scan, during which time 160 readings may be made by each detector, the total number of readings obtained is equal to the number of detectors times 160. The increment of angular rotation between views can be significantly larger than with a first generation unit, up to as much as 36°. Thus, the number of distinct rotations of the scanning apparatus can be significantly reduced, with a coincidental reduction in scanning time. By gathering more data per translation, fewer translations are needed.
To obtain even faster scanning times it is necessary to eliminate the complex translational-rotational motion of the first two generations. Third generation scanners therefore use a much wider, “divergent” fan beam. In fact, the angle of the beam may be wide enough to encompass most or all of an entire patient section without the need for a linear translation of the x-ray tube and detectors. As in the first two generations, the detectors, now in the form of a large array, are rigidly aligned relative to the x-ray beam, and there are no translational motions at all. The tube and detector array are synchronously rotated about the patient through an angle of 180-360°. Thus, there is only one type of motion, allowing a much faster scanning time to be achieved. After one rotation, a single tomographic section is obtained.
Fourth generation scanners also feature a divergent fan beam similar to the third generation CT system. As before, the x-ray tube rotates through 360° without having to make any translational motion. However, unlike in the other scanners, the detectors are not aligned rigidly relative to the x-ray beam. In this system only the x-ray tube rotates. A large ring of detectors are fixed in an outer circle in the scanning plane. The necessity of rotating only the tube, but not the detectors, allows faster scan time.
Beyond these large “generational” distinctions between CT technology, a number of additional advancements have been made. For example, dual energy and even dual source CT systems have been developed. In either case, x-ray dose of different energy levels are used to acquire two image data sets from which a low energy and a high energy image may be reconstructed. As will be described, a wide variety of information can than be determined from the subject by analyzing the characteristics and variations between the low energy data set and the high energy data set.
In addition, photon counting (PC) and energy discriminating (ED) detector CT systems have the potential to greatly increase the medical benefits of CT. Unlike the above-described “traditional” CT detectors, which integrate the charge generated by x-ray photon interactions in the detector but provide no specific energy information regarding individual photons, PC detectors record the energy deposited by each individual photon interacting with the detector. PC detector system can provide new clinical abilities due to an ability to differentiate materials such as a contrast agent in the blood and calcifications that may otherwise be indistinguishable in traditional CT systems. Also, they can improve the signal to noise ratio (SNR) by reducing electronic and swank noise. PC and ED CT systems generally produce less image noise for the same dose than photon energy integrating detectors and hence can be more dose efficient than conventional CT systems. Also, they can improve SNR by assigning optimal, energy dependent weighting factors to the detected photons and achieve additional SNR improvements by completely or partially rejecting scattered photons. Further still, PC detectors allow measurement of transmitted, energy-resolved spectra from a single exposure at one tube potential.
The development of PC detectors for micro-CT and whole-body CT applications has enabled a new dimension of CT imaging, namely “spectral CT” or “multi-energy CT.” These advances have attracted considerable attention in the scientific and research communities, due to the potential for enhanced material characterization utilizing spectral x-ray information. This lays the groundwork for many clinical applications, such as detecting new biomarkers, such as iron in vulnerable plaque, multi-contrast imaging, such as iodine and barium imaging of the bowel luminal wall and intra-lumen contents, and exploring intrinsic tissue contrast, cancerous tissue compared to normal tissue.
In contrast to conventional CT systems, where photons are measured and recorded in a single transmission data set, spectral CT generates multiple data sets, with each data set measuring only those photons with energies between predefined low and high energy thresholds. Because the x-ray attenuation of a material depends on the photon energy, material-specific information is then built into each energy-specific data set. Measured data from each energy bin is then reconstructed independently to generate a series of CT images, each corresponding to a specific energy range. These images are highly correlated, since the anatomic geometry and physical density of the object remains unchanged for any time point. Only the total x-ray attenuation values, that is, CT numbers, differ, according to the material type and selected photon energy bin. An attenuation-energy curve can be generated from these multiple image series, each image corresponding to one energy bin. Since each material has its own attenuation-energy curve, material identification/differentiation can then be achieved using multi-energy CT.
The appropriate selection of energy bins, for example, the number of energy bins and width of each energy bin, has a significant affect on the outcome of spectral imaging. A narrow energy bin has better energy resolution compared to a wider energy bin, and hence enables better material identification/differentiation. For example, FIG. 1 shows a graph of two energy bins used to separate iron, which is a biomarker for vulnerable plaques, from calcium. A narrow energy window width of 20 keV was used and the two energy bins were widely separated in the x-ray spectrum. The dual energy ratio difference, which is an indicator of material separation capability, or the dual-energy “contrast” between two materials, using these energy windows were compared with conventional dual energy CT, in which wider energy windows, with a low of 0 to 80 kVp and an high of 0 to 140 kVp were used. Significant improvement was observed using the narrow beam energy windows (20 keV). However, a significant limitation of using narrow bins is that the number of photons available in each energy bin is much smaller than the total number of photons detected. For the scenario in FIG. 1, only a small portion of total photons were used in each energy-specific image and a large fraction of photons in between energy bin 1 and 2 were discarded.
As image noise is proportional to the inverse square root of available photons, image noise is correspondingly higher using a narrow energy bin than a wide energy bin. Thus, a critical problem occurs. Specifically, in order to identify or differentiate materials using spectral CT, the differences in effective atomic number or signal must be amplified by: 1) using narrow energy bins and 2) separating the energy bins as widely as possible. However, this requirement excludes a large percentage of the detected energy spectrum from the considered image data. Thus, the resultant images, in which dual-energy signal is increased, suffer from increased noise. For narrow energy bins, especially in the lower energy range, the image noise may be so high as to make it impossible to detect small differences in material composition, that is, the signal to noise ratio (SNR) is too low. Further, a large portion of the dose delivered to the patient is wasted, creating a difficult dilemma of the clinician balancing between dose delivered and achieving a desired SNR. Thus, the requirements for increasing dual-energy signal are in direct conflict with the requirements for decreasing image noise in the individual energy images and in any material composition images derived from the energy specific images.
Similar observations exist for the selection of total number of energy bins. For a given x-ray spectrum, a given kVp, more energy bins provide more measurements of energy dependent information. With multiple data points available along the attenuation-energy curve, better curve-fitting, consequently better material differentiation is achieved. However, more bins also dictates narrower widths for each bin and hence fewer photons in each bin. Turning to FIG. 2, a scenario in which 6 energy bins were used is illustrated. In FIG. 2, 6 separate measurements in the energy domain corresponding to the 6 energy bins are available. However, the number of photons in each energy bin is only ⅙ of the total photons delivered. Accordingly, the noise in each image is then significantly high.
Therefore, an intrinsic tradeoff exists in the selection of energy bins (number, width, and placement) for spectral CT, resulting in the described tradeoff between energy-specific signal (material identification/differentiation information) and noise. This tradeoff limits the clinical applications of spectral CT. For example, for the differentiation between iron (a biomarker for plaque vulnerability) from calcium in vascular plaques, narrow energy bins are generally used due to the very small concentration iron amidst a typically higher concentration of calcium (i.e. there is a very weak signal). Due to the small signal size, image noise must be strictly controlled to allow the detection of iron, and hence the identification of those plaques more likely to rupture and cause acute myocardial infarction. Thus, a dilemma is presented of increasing signal size through appropriate selection of the energy bins is counterproductive due to the increase in image noise. Although increased photons (dose) could potentially be used, increases in patient dose above existing levels will prevent clinical application due to the heightened concern about ionizing radiation in medicine and potential long-term effects of such radiation on patients. An increased dose will also likely require higher power and cooling requirements on the x-ray tube and generator, as current coronary CT angiography already uses the upper limits of tube/generator technology. Addressing this with use of longer scan times, such as using longer gantry rotation times, would sacrifice image quality with motion artifact and hence blur out the small signal that is sought.
Accordingly, it would be desirable to have a system and method for creating an energy series of images with reduced noise and increased signal to noise ratio.